查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Bangi, Malaysia, by NewsRx journalists, research stated, “The smart grid (SG) is an advanced cyber-p hysical system (CPS) that integrates power grid infrastructure with information and communication technologies (ICT). This integration enables real-time monitor ing, control, and optimization of electricity demand and supply.” The news reporters obtained a quote from the research from the University of Keb angsaan, “However, the increasing reliance on ICT infrastructures has made the S G-CPS more vulnerable to cyberattacks. Hence, securing the SG-CPS from these thr eats is crucial for its reliable operation. In recent literature, machine learni ng (ML) techniques and, more recently, deep learning (DL) techniques have been u sed by several studies to implement cybersecurity countermeasures against cybera ttacks in SG-CPS. Nevertheless, the achieving high performance of these state-of -the-art techniques is constrained by certain challenges, including hyperparamet er optimization, feature extraction and selection, lack of models’ transparency, data privacy, and lack of real-time attack data. This paper reviews the advance ment in using ML and DL techniques for cybersecurity countermeasures in SG-CPS. It analyzes the constraints that need to be addressed to improve performance and achieve real-time implementation. The various types of cyberattacks, cybersecur ity requirements, and security standards and protocols are also discussed to est ablish a comprehensive understanding of the cybersecurity context in SG-CPS.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Com putational Intelligence is the subject of a report. According to news reporting from Birmingham, United Kingdom, by NewsRx journalists, research stated, “Differ ent from most other dynamic multi-objective optimization problems (DMOPs), DMOPs with a changing number of objectives usually result in expansion or contraction of the Pareto front or Pareto set manifold. Knowledge transfer has been used fo r solving DMOPs, since it can transfer useful information from solving one probl em instance to solve another related problem instance.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Intelligent Systems have been published. According to news reporting from Changchun, People’s Republic of China, by NewsRx journalists, research stated, “ Inferring the 3D surface shape of a known template from 2D images captured by a monocular camera is a challenging problem. Due to the severely underconstrained nature of the problem, inferring shape accurately becomes particularly challengi ng when the template exhibits high curvature, resulting in the disappearance of feature points and significant differences between the inferred and actual defor mations.” Financial supporters for this research include Natural Science Foundation of Jil in Province, Jilin Provincial Natural Science Foundation.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on artificial intelligence is now ava ilable. According to news reporting out of the Department of Civil Engineering b y NewsRx editors, research stated, “This study planned to predict and analyze th e driver injury severity (DIS) using twelve machine learning (ML) algorithms.” The news editors obtained a quote from the research from Department of Civil Eng ineering: “Police reports of single and two-vehicle accidents that occurred duri ng 2011-2020 in the two cities of India (Itanagar and Imphal) were used in this study. The best-performing model to predict the DIS for Itanagar was Gradient Bo osting Trees (GBT). ‘Causes of Accident’ variable had shown maximum impact on th e DIS. In the case of Imphal, it was the GBT, Extra Trees, and Random Forest mod els across all k-fold cross-validation for train ratios 0.70, 0.80, and 0.90, re spectively. ‘Causes of Accident’, and ‘Vehicle Type’ had shown maximum impact on the DIS.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Stuttgart, Germany, by NewsRx editors, research stated, “Diffusion coefficients of electrode materials are often determined using galvanostatic (GITT) or potentiostatic intermittent titration technique (PITT), electrochemical impedance spectroscopy (EIS) or cycl ic voltammetry (CV). However, these methods require special care as for each, th eir formal derivations use quite restrictive assumptions.” Financial support for this research came from German Research Foundation (DFG).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics have been pr esented. According to news reporting out of Nanjing, People’s Republic of China, by NewsRx editors, research stated, “On-site assembly of prefabricated componen ts is crucial for the construction efficiency and quality of prefabricated build ings. In this process, a prefabricated component is first lifted and transported to the vicinity, where it will be installed using a crane.” Funders for this research include National Natural Science Foundation of China ( NSFC), Carbon Emission Peak and Carbon Neutrality Innovative Science Foundation of Jiangsu Province “The key research and demonstration projects of future low - carbon emission buildings”, Fundamental Research Funds for the Central Universit ies.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics - Ro botics and Automation have been published. According to news reporting from Stan ford, California, by NewsRx journalists, research stated, “Learningbased models for robot perception are known to suffer from two distinct sources of error: al eatoric and epistemic. Aleatoric uncertainty arises from inherently noisy traini ng data and is easily quantified from residual errors during training.” Financial support for this research came from Defense Advanced Research Projects Agency (DARPA). The news correspondents obtained a quote from the research from Stanford Univers ity, “Conversely, epistemic uncertainty arises from a lack of training data, app earing in out-of-distribution operating regimes, and is difficult to quantify. M ost existing state estimation methods handle aleatoric uncertainty through a lea rned noise model, but ignore epistemic uncertainty. In this work, we propose: (i ) an epistemic Kalman filter (EpiKF) to incorporate epistemic uncertainty into s tate estimation with learned perception models, and (ii) an epistemic belief spa ce planner (EpiBSP) that builds on the EpiKF to plan trajectories to avoid areas of high epistemic and aleatoric uncertainty. Our key insight is to train a gene rative model that predicts measurements from states, ‘inverting’ the learned per ception model that predicts states from measurements. We compose these two model s in a sampling scheme to give a well-calibrated online estimate of combined epi stemic and aleatoric uncertainty.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Pittsburgh, Penns ylvania, by NewsRx journalists, research stated, “Generative Artificial Intellig ence has made significant impacts in many fields, including computational cognit ive modeling of decision making, although these applications have not yet been t heoretically related to each other. This work introduces a categorization of app lications of Generative Artificial Intelligence to cognitive models of decision making.” Financial support for this research came from Army Research Office. The news correspondents obtained a quote from the research from Carnegie Mellon University, “This categorization is used to compare the existing literature and to provide insight into the design of an ablation study to evaluate our proposed model in three experimental paradigms. These experiments used for model compari son involve modeling human learning and decision making based on both visual inf ormation and natural language, in tasks that vary in realism and complexity. Thi s comparison of applications takes as its basis Instance-Based Learning Theory, a theory of experiential decision making from which many models have emerged and been applied to a variety of domains and applications. The best performing mode l from the ablation we performed used a generative model to both create memory r epresentations as well as predict participant actions. The results of this compa rison demonstrates the importance of generative models in both forming memories and predicting actions in decision-modeling research. In this work, we present a model that integrates generative and cognitive models, using a variety of stimu li, applications, and training methods.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics are presented i n a new report. According to news reporting out of Sathyamangalam, India, by New sRx editors, research stated, “Enforcement of advanced deep learning methods in hand-object pose estimation is an imperative method for grasping the objects saf ely during the human-robot collaborative tasks. The position and orientation of a hand-object from a two-dimensional image is still a crucial problem under vari ous circumstances like occlusion, critical lighting, and salient region detectio n and blur images.” Our news journalists obtained a quote from the research from the Bannari Amman I nstitute of Technology, “In this paper, the proposed method uses an enhanced Mob ileNetV3 with single shot detection (SSD) and YOLOv5 to ensure the improvement i n accuracy and without compromising the latency in the detection of hand-object pose and its orientation. To overcome the limitations of higher computation cost , latency and accuracy, the Network Architecture Search and NetAdapt Algorithm i s used in MobileNetV3 that perform the network search for parameter tuning and a daptive learning for multiscale feature extraction and anchor box offset adjustm ent due to auto-variance of weight in the level of each layers. The squeeze-and- excitation block reduces the computation and latency of the model. Hard-swish ac tivation function and feature pyramid networks are used to prevent over fitting the data and stabilizing the training. Based on the comparative analysis of Mobi leNetV3 with its predecessor and YOLOV5 are carried out, the obtained results ar e 92.8% and 89.7% of precision value, recall value o f 93.1% and 90.2%, mAP value of 93.3% a nd 89.2%, respectively.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news reporting originating in Shandong, People’s Republic of China, by NewsRx journalists, research stated, “In order to reduce the treat ment cost required for the recovery of patients with nerve injury, a rehabilitat ion training robot based on single-degree-of-freedom eight-link leg mechanism is proposed. The robot imitates human gait by repeatedly and naturally moving the legs.” The news reporters obtained a quote from the research from the Shandong Universi ty of Science and Technology, “Clinical cases show that this training can help p atients to carry out targeted exercises, such as leg activity exercises, improvi ng balance, physical training and so on. The motion cycle of the mechanism is ma tched with the generalized gait cycle in clinic. Then, based on the support phas e and swing phase of the gait cycle, the mechanism is optimized by adjusting the link length through kinematic analysis. The theoretical calculation and virtual simulation are carried out by using SOLIDWORKS, MATLAB and ADAMS software, and the feasibility of the mechanism is verified.”
NETL
NSTL